The problem with the ordinary tiled-layout views is about the possible re-arrangement of the tiles, thus an user might see a different result upon the actual viewport size. I needed something “fixed” instead. The user should define the layout by editing the grid via drag-and-drop, then that layout will be fixed for any screen. However, the editor should consider more than a single arrangement, whereas the feasible displays can’t fit the desired layout.

The demo leverages an useful MVVM pattern, and allows to define several kind of blocks: fixed, full-sizable, shrinkable, expandable, on just one or both the directions.

The library is working, but at the moment as a beta (several minor problems and refinements to work on). A reasonable prototype to put your hands on, though.

As described, the project is tailored for the Universal Windows Platform, so only Windows 10 (phones and IoT as well) is supported. You must use Visual Studio 2015 on Windows 10 for development also.

Editing mode (drag-and-drop to add/move/remove tiles)Blocks size is modifiable at any timeThe view mode: as any normal hub page.

This is my first post about Windows 10 IoT and small computers (embedded) after some experiences in the past with the .Net MicroFramework (Netduino, in essence).

I must say that this Windows 10 is finally a small masterpiece, or “everything you ever asked and none never responded you”. The programming way is easy but very flexible, although still many bricks are missing (in development).

Here is a very simple experiment, a bit vintage, of driving a common alphanumeric LCD module (HD44780-based) with a Raspberry PI 2 and Windows 10 IoT.

The project isn’t anything new, but rather kinda “refresh” of another of mine where the Netduino board was used (see below). Someone of you may wonder “why” still using a so-old LCD module when several graphics are available on the market. Well, my first answer is: “why not?”. As said, this project hasn’t any specific purpose (although many of you may dig into their “miracles box” and pull out an “almost useless” LCD module). The aim is to test how hard is to drive something well known.

Some credits…

I can’t miss to mention Laurent Ellerbach, who gave me some inspiration (and motivation) on pursuing those hacking/funny activities.

The hardware.

All you need is very easy to find:

Raspberry PI2 (with Windows 10 IoT installed)

any suitable HD44780 LCD display module (mine is a 4×20)

74HC595 shift-register

220 Ohms resistor (only if you need the backlight)

10k Ohms trimpot (22k or 47k are fine the same)

For sake of simplicity, I won’t detail how to set up the Raspberry, but there are many articles which describe very well that. I followed the Microsoft site and everything went fine, except for the suggested SD minimum size: I found that a 8GB won’t work. Simply consider a 16GB.

The software.

I wanted to publish the project keeping the sources simpler as possible. A similar application won’t have sense in a complex hardware (full-featured TFT displays and HDMI monitors perform way better than this module). The general guideline is: if you find convenient to connect a LCD module to a RPI, then make it working in minutes.

Since the LCD module’s capabilities are very limited, I embraced the idea to expose the APIs as it were a kind of “Console”. Just a “write” and something more, where a background task should manage the physical transfer by itself.

The project contains two different demo:

a basic one, where some strings’ content is reflected on the display;

a slightly more complex demo, which gets a bunch of RSS news from the BBC.uk channel, and rotates the titles on the screen.

Performance.

You may wonder how well performs the driver. Well, there are two stages involved in the displaying process:

the calls from the main application to the driver;

the physical data transfer.

Any invokation by the main app involves always the cache: no matter how many calls are made, because everything is hosted in memory. For this reason, any manipulation is irrelevant in terms of performance impact. However, a fixed rate (typically 200ms) there’s a cache dump to the LCD screen, that is: the physical data transfer though the SPI.

How long takes the entire screen dump via SPI?

The circuit is very simple, thus there’s no way to take the transfer faster than the machine execution speed. Even adjusting the SPI clock rate, the resulting duration won’t change notably. Please, bear in mind that a too high SPI clock rate could face signal degradation due the wire length. I used a perfect 1 MHz value, and you can see from the below screenshot that the total transfer duration is less than 30ms.

If you are interested in a faster way to dump the data via SPI, I suggest to read the following section which requires a decent knowledge about electronics.

The old “LCD Boost” library.

The original project was tailored for the .Net MicroFramework (Netduino) and many things were optimized for speed reasons. Moreover, the NetMF had some leaky problems mostly due to the super squeezed CLR, thus many solutions were solved as it were a low-level device.

Here is just another misleading faces of the JavaScript (or, better, EcmaScript).
Ten years ago or so, I probably had a better consideration of this language, but I really cannot avoid to compare it with C#. The strong yet clear rules of C# rarely lead to side-effects like this one.

Function: gimme your reference!

As in C#, a function can be referred using a delegate, and its “pointer” is uniquely identified in the program. The same thing is in C/C++: you can refer to a certain function by a simple pointer.
In JavaScript isn’t so simple, because the functions are instantiated on every scope creation. This leads to problems when you wish to subscribe and unsubscribe callbacks, events, and similar.
Honestly, I was unaware about this problem, and I bumped against it using the Socket.io library. Simply I wanted to unsubscribe the events (callbacks) from a socket, but the handler functions were nested inside another function. The result is plain simple: the unsubscription failed.

A neat example…

Consider this minimal pattern for subscribe/unsubscribe a single callback:

As said, the reason is that the “handler” function is instantiated (as a new “object”) every time the containing function “f” is called. Thus, the first “handler” reference won’t be the same as the second call.

Conclusions.

You will say: “that’s fine: it’s all about the language!”. Then I’ll answer: “Okay: may I say that I don’t like that?”.

This is my very first post about “pure-web” tech, and it’s also very short. I began to deal with those things some months ago, but I feel there’s a long road to walk.
Here is an attempt to re-think the Single-Page (web) Application (a.k.a. SPA) using Angular-JS, toward a more abstracted templating way. The reasons behind a similar solution are pretty hard to understand only reading this post, but shortly I’ll post a much larger yet concrete framework for telemetry applications.
As a hint, think the ability to compose a page from a series of components, and store/retrieve the layout on any persistent medium (e.g. file, database, etc)

From what I meant, AngularJS is among the closest web-frameworks to the desktop’s WPF, which is (at least in my mind) the best framework for LOB apps.
However, I noticed that the ability to reuse components, abstract views and so away, is still somewhat not yet standardized, nor used. That’s because I thrown myself in this challenge, and the result isn’t bad as expected (for a web-dev noob like me).
A short video should explain way better than thousand words how the result is:

In this article I’ll show you how to setup some components of Windows Azure, in order to make the system working.

I won’t cover details such as “how to subscribe to the Azure platform” or similar. Please, consider the several posts around the web, that describes very well how to walk the first steps, as well the benefits coming from the subscription.
A good place to start is here.

The system structure more in depth.

In the previous article there is almost no description about the system structure, mainly because the post is focused on the device. However, since here the key-role is for Azure, it’s better to dig a bit in depth around what’s the target.

On the left there are a couple of Netduinoes as symbol of a generic, small device which interfaces with sensors, collects some data, then sends them to the Azure platform. This section is covered in the first part of the series.
The JSON-over-HTTP data sent by any device are managed by a “custom API” script within the Azure’s “Mobile Services” section. Basically a Node.JS JavaScript function which is called on every device’s HTTP request.
This script has two major tasks to do:

parse the incoming JSON data, then store them into a SQL database;

“wake-up” the webjob, because new data should be processed.

The database is a normal Azure SQL instance, where only two simple tables are necessary for this project. One is for holding the current variables state, that is every single datum instance incoming from any device. The other table depicts the “history” of the incoming data, that is the evolution of the state. This is very useful for analysis.

Finally, there is the “webjob”.
A webjob could be seen as a service or, more likely, as a console application. You can put (almost) anything into this .Net app, then it can started anytime. What I need is something like a endlessly running app, but in a “free-context” this service is shut-down after 20-30 minutes. That’s the way I used a trick to “wake it up” using kinda trigger from the script. Whenever new data are incoming the app is started, but can stay stopped whenever nothing happens.
The webjob task is just sending a mail upon a certain condition is met. In this article I won’t show anything sophisticated, than a very short plain-text mail. The primary goal here is setting up the Azure platform, and testing the infrastructure: in the next articles we’ll add several pieces in order to make this project very nice.

Looks nice, but…how much does cost all that?

Just two words about the cost of the Azure platform.
Entering into the Azure portal is much like as walking in Venezia: full of intriguing corners, each one different from others, and always full of surprises. The platform is really huge, but surprisingly simple to use.

I say that I was surprised, because you’ll be also surprised by realizing that many stuffs come for FREE. Unless you want to scale up (and get more professional) this project, your bill will stick to ZERO.

Setup the mobile service.

The Mobile Services are the most important components in order to interface any mobile device. The “mobile” term is rather oriented to devices like phones or small boards, but the services could be accessed even from a normal PC.
The first thing to do is create your own mobile service: this task couldn’t be more easy…

Type in your favorite service name, which has to be an unique identifier worldwide (as far I know).
About the database, ensure to pick the “Create a free 20 MB SQL database” (if you don’t have one yet), and the wizard will create automatically for you.
Two more parameters: select the closest region to you to host the service, then choose “JavaScript” as backend language for the management.

If you are creating a new database, you’ll face a second page in the wizard. Simply you have to specify the credentials to use to gain access to the database.

That’s all: within a few your brand new mobile service should be ready. The below sample view gives an overview about the service.

Please, notice that there are links where you can download sample apps/templates already configured with your own parameters!…Dumb-proof!

Also have a look at the bottom toolbar, where a “manage keys” button pops up some strange strings. Those strings are the ones that you should specify in the Netduino (and any other device) in order to gain access to the Azure Mobile Service.

The next task to do is about creating the database tables.
We need just three tables, and (even surprising) we don’t need to specify any column-schema: it will created automatically upon the JSON structure defined in the Netduino device software. This feature is by default, but you can disable it in the “configure” section, with the “dynamic schema” switch.

Table name

Purpose

tdevices

Each record is paired to a remote device and holds identification and status data of it.

tsensors

Each record is paired to a “variable” defined by a certain device somewhere and holds identification and status data of it.

thistory

Each record stores the value of a certain variable at the time it arrives on the server, or marks an event occurred. Think the table as a queue, where you can query the records in order to depict a certain variable’s value evolution over time.

Press “create” and enter “tsensors”, then ensure checked the “enable soft delete” and confirm. Repeat the same for both the “tdevices” and the “thistory” tables, and your task is over.
The “soft delete” feature marks a record as “deleted” and keeps it, instead of removing from the table. You should enable this feature when you deal with concurrency. I personally think it is useful even for a simple dubugging. The problem is that is up to you “cleaning” the obsolete records.

The last section to setup within the Mobile Service context is the “Custom API“, that is the code to run upon any incoming data request.
Simply select the “API” section, then press “create”.

The wizard will ask you the name of the new API, as well as the permission grants to access it.
Back to the Netduino code, the API’s name should be specified on any request.

Technically speaking, the name is the very last segment of the URI path which maps the request against Azure.

http://{your-service-name}.azure-mobile.net/api/{your-api-name}

At this point you can begin to type the script in.

The device-side entry-point for the data.

The handler for the incoming requests is just a JavaScript function. Better: one function per HTTP method. However, since the primary goal is pushing data from a device into the server, the method used is POST (CREATE, in the REST terminology) all the times.
The JavaScript environment comes with Node.Js, which is very easy yet compact to use. I’m NOT a JavaScript addict, but honestly I didn’t have much effort in coding what I wanted.
The “script” section of the API allows to edit your script as you were on Visual Studio. The only missing piece is the Intellisense, but for JavaScript I don’t need it actually.

As the data come in, the first thing is to look for the correspondent existent entry in the “tdevices” table, using the device’s identification as key. If the record does exist, it will be “updated”, otherwise a new entry will be added.
Upon an update, the logic here is comparing the incoming “configuration” version with the corresponding value stored in the table. If they don’t match, the “flush” flag is set, which serves to the next step to remove all the obsolete “sensor” entries.

When the operation on the “tdevices” table is over, begins the one on the “tsensors” and the “thistory” tables.
As in the previous snippet, first there is a selection of the records of “tsensors” marked as owned by the current device identifier. Then, if the “flush” flag is set, all the records are (marked as) deleted.
Finally, the data contained in the incoming message are scanned one item at once. For each variable, it looks for the corresponding entry in the recordset, then either update it or add a new record if wasn’t found.
Any item present in the message is also appended “as-is” to the “thistory” table.

The last but not least piece of script is for waking up the webjob.
Please, note that my usage of the webjob is rather uncommon, but I think it’s the best compromise. The trade is between the Azure “free-context” limitations, and the desired service availability. The result is a webjob configured as “running continuously”, but is shut down by the platform when there’s no external “stimulation”. The trick is to “wake up” the webjob only when necessary by invoking a fake call to its site.
Have a look at my question on StackOverflow on how to solve the problem.

At the end, it’s a trivial dummy read to the webjob deployment site. This read wakes up or keeps awaken the webjob.

Please, notice that all the “console” calls are useful only during the debugging stage: you should remove them when the system is stable enough.

If everything goes well, the Netduino should send some data to the Azure API, and the database should fill.
Here is an example of what the “tsensors” table may contain:

Creating and deploying the webjob.

To understand what a “webjob” is, I suggest to read the Scott Hanselman’s article.
Since a webjob is part of a web-site, you must create one first. Azure offers up to 10 web-sites for free, so that isn’t a problem. At the moment, I don’t use any “real” web-site (meaning pages), but I need the registration.
The procedure of registration, deployment and related task can be easily managed from within Visual Studio.

When I started the project I used Visual Studio Express 2013 for Web, and the Update 4 CTP allowed such a management. Since a few days, there’s another great alternative: Visual Studio 2013 Community, which comes out with Update 4 released, but offers also a lot of useful features.
The following snapshots were taken on the Express release, but should be similar on other editions.

Start Visual Studio and create a “Microsoft Azure Webjob” project, and give it the proper name.

As you may notice, the solution composition looks almost the same as a normal Console application.
In order to add the proper references, just choose the “Manage NuGet packages” from the project’s contextual menu.

Since this webjob will “run continuously”, but will be actually shut down often, the very first thing to add to the code is a procedure for detecting the shutting request, so that to exit the application gracefully.
This piece of code isn’t mine, so I invite to read the original article by Amit Apple about the trick.

At this point you might add some blocking code, and test what happens. As in the Amit’s article:

// Run as long as we didn't get a shutdown notification
while (isRunning)
{
// Here is my actual work
Console.WriteLine("Running and waiting " + DateTime.UtcNow);
Thread.Sleep(1000);
}
Console.WriteLine("Stopped " + DateTime.UtcNow);

Before deploying the webjob onto Azure, we should check the “webjob-publish-settings” file which is part of the project. Basically, we should adjust the file in order to instruct the server to run the webjob continuously. Here is an example:

Open the project’s contextual menu, and choose the “Publish as Azure Webjob” item. A wizard like this one will open:

We should specify the target web-site from this dialog:

If the web-site is not existent yet, we should create a new one:

When everything has been collected for the deployment, we can validate the connection, then proceed to the publication.

Once the webjob has been published, it should placed to run immediately. To test whether the shut down will happen gracefully, simply leave the system as is, and go to take a cup of coffee. After 20-30 minutes, you can check what really happened in the webjob’s log.

Please, note that it’s important that you leave any webjobs’ status page of the Azure portal during the test. It would hold alive the service without really shutting it down.

Enter in the “websites” category, then in the “Webjobs” section:

At this point you should see the status as “running” or being changing to. Click the link below the “LOGS” column, and a special page will open:

This mini-portal is a really nice diagnostic tool for the webjobs. You should able to trace both explicit “Console” logs and also exceptions. To reveal the proper flow of the webjob, you should check the timestamps, as well as the messages such as:

[11/03/2014 07:03:53 > bb4862: INFO] Stopped 11/3/2014 7:03:53 AM

The mail alert application.

Most of the material inherent to this article has been shown. However, I just would to close this part with a “concrete” sign of what the project should do. On the next article I’ll focus almost entirely on the webjob code, where the system could considered finished (many things will follow, though).

As described above, as soon a message from any device calls the API, the webjob is waken up (in case is stopped), and the data are pushed in the database.
The webjob task should pick those data out, and detect what is changed. However, the API and the webjob execution are almost asynchronous each other, so it’s better to leave the webjob running and polling for other “news”. On the other hands, when something changes by a remote point, it might be possible that something else will change too in a short time. This is another reason for leaving the webjob running until the platform shuts it down.

I don’t want to dig into details here: this will be argument for the next article. The only important thing is how the data are read periodically (about 10 seconds here) from the server. The data read are copied in a local in-memory model, for ease of interaction with the language.
At the end of each poll, the variable which are changed since the previous poll are marked with the corresponding flag. Immediately after, the program flow yields the execution of a custom logic, that is what the system should do upon a certain status.

Let’s say that this piece of code is “fixed”. Regardless what the system should react upon the status, this section will be always the same. For this reason there’s a special, well-defined area where we could write our own business logic.
Here is a very simple example:

If you remember, the “Analog0” and “Analog1” are two variables sent by the Netduino. When I turn the trimpots so that:

any of the two variables is detected as changed, and…

the “Analog0” value becomes greater than the “Analog1” value…

…then an e-mail message is created and sent to me…(!)

Here is what I see on my mailbox:

Conclusions.

This article looks long, but it isn’t actually so: there are a lot of picture because the Azure setup walkthrough.
Azure experts may say that a more straightforward solution would be using a Message-Hub instead of a tricky way to trigger a webjob. Well, yes and no. I didn’t find a way to “peek” what’s inside a queue without removing its content, as long as other problems to solve.
This is much more an experimental project built on the Azure “sandbox”, than a definitive optimal way to structure a telemetry system. However, I believe that’s a very good point to start, take practice, then refine your own project.

In the next article, I’ll show how to create a better (yet useful) mail alerting component.

This is the the first part of a series, where I’ll present a telemetry project as a classic “Internet of Things” (IoT) showcase. The project starts as very basic, but it’ll grow up in the next parts by adding several useful components.
The central-role is for Microsoft Azure, but other sections will space over several technologies.

The source of the project is hosted in the azure-veneziano GitHub repository.

Inspiration.

This project was born as a sandbox for digging into cloud technologies, which may applies to our control-systems. I wanted to walk almost every single corner of a real control-system (kinda SCADA, if you like), for understanding benefits and limitations of a full-centralized solution.
By the way, I was also inspired by my friend Laurent Ellerbach, who published a very well-written article on how to create your own garden sprinkler system. Overall, I loved the mixture of different components which can be “glued” (a.k.a. interconnected) together: it seems that we’re facing a milestone, where the flexibility offered by those technologies are greater than our fantasy.At the time of writing, Laurent is translating his article from French to English, so I’m waiting for the new link. In the meantime, here’s an equivalent presentation who held in Kiev, Ukraine, not long ago.

Why the name “Azure Veneziano”?

If any of you had the chance to visit my city, probably also saw in action some of the famous glass-makers of Murano. The “Blu Veneziano” is a particular tone of blue, which is often used for the glass.
I just wanted to honor Venezia, but also mention the “color” of the framework used, hence the name!

The system structure.

The system is structured as a producer-consumer, where:

the data producer is one (or more) “mobile devices”, which sample and sometime collect data from sensors;

the data broker, storage and business layer are deployed on Azure, where the main logic works;

the data consumers are both the logic and the final user (myself in this case), who monitor the system.

In this introductory article I’ll focus the first section, using a single Netduino Plus 2 board as data producer.

Netduino as the data producer.

In the IoT perspective, the Netduino plays the “Mobile device” role. Basically, it’s a subject which plays the role of a hardware-software thin-interface, so that the converted data can be sent to a server (Azure, in this case). Just think to a temperature sensor, which is wired to an ADC, and a logic gets the numeric value and sends to Azure. However, here I won’t detail a “real-sensor” system, rather a small simulation as anyone can do in minutes.
Moreover, since I introduced the project as “telemetry”, the data flow is only “outgoing” the Netduino. It means that there’s (still) no support to send “commands” to the board. Let’s stick to the simpler implementation possible.

The hardware.

The circuit is very easy.

Two trimpots: each one provide a voltage swinging from 0.0 to 3.3 V to the respective analog input. That is, the Netduino’s internal ADC will convert the voltage as a floating-point (Double) value, which ranges from 0.0 to 100.0 (for sake of readiness, meaning it as it were a percent).
There are also two toggle-switches. Each one is connected to a discrete (Boolean) input, which should be configured with an internal pull-up. When the switch is open, the pull-up resistor takes the input value to the “high” level (true). When the switch is closed to the ground, it takes the value to the “low” level, being its resistance lower than the pull-up. and two switches.
If you notice, there’s a low-value resistor in series to each switch: I used a 270 Ohms-valued, but it’s not critical at all. The purpose is just to protect the Netduino input from mistakes. Just imagine a wrong setting of the pin actually configured as an output: what if the output would set the high-level when the switch is closed to the ground? Probably the output won’t fry, but the stress on that port isn’t a good thing.

All those “virtual” sensors can be seen from a programmer perspective as two Double- and two Boolean-values. The funny thing is that I can modify their value with my fingers!

Again, no matter here what could be the real sensor. I’d like to overhaul the hardware section for those who don’t like/understand so much about electronics. There are many ready-to-use modules/shields to connect, which avoid (or minimize) the chance to deal with the hardware.

Some virtual ports and my…laziness.

Believe me, I’m lazy.
Despite I’m having a lot of fun by playing with those hardware/software things, I really don’t like to stay spinning all the time the trimpots or sliding the switches, but I need some data changing overtime. So, I created a kind of (software) virtual port.
This port will be detailed below, and its task is to mimic a “real” hardware port. From the data production perspective it’s not different from the real ports, but way easier to manage, especially in a testing/demo session.
This concept of the “virtual port” is very common even in the high-end systems. Just think to a diagnostic section of the device, which collects data from non-physical sources (e.g. memory usage, cpu usage, etc)

The software.

Since the goal is posting on a server the data read by the Netduino, we should carefully choose the best way to do it.
The simplest way to connect a Netduino Plus 2 to the rest of the world is using the Ethernet cable. That’s fine, at least for the prototype, because the goal is reach the Internet.
About the protocol, among the several protocols available to exchange data with Azure, I think the simplest yet well-known approach is using HTTP. Also bear in mind that there’s no any “special” protocol in the current Netduino/.Net Micro Framework implementation.
The software running in the board is very simple. It can be structured as follows:

the main application, as the primary logic of the device;

some hardware port wrappers as data-capturing helpers;

a HTTP-client optimized for Azure-mobile data exchange;

a JSON DOM with serialization/deserialization capabilities;

The data transfer is normal HTTP. As the time of writing, the .Net Micro-Framework still did not offer any HTTPS support, so the data are flowing unsecured.

The first part of the main application is about the ports definition. It’s not particularly different than the classic declaration, but the ports are “wrapped” with a custom piece of code.

The class derives from the original AnalogInput port, but exposes the “Sample” method to capture the ADC value (Read method). The purpose is similar to a classic Sample-and-Hold structure, but there is a compare algorithm which detect the new value’s variation.
Basically, a “tolerance” parameter (normalized) has to be defined for the port (default is 5%). When a new sample is performed, its value is compared in reference to the “old value”, plus the tolerance-window around the old-value itself. When the new value falls outside the window, the official port’s value is marked as “changed”, and the old-value replaced with the new one.
This trick is very useful, because allows to avoid useless (and false) changes of the value. Even a little noise on the power rail can produce a small instability over the ADC nominal sampled value. However, we need just a “concrete” variation.

The above class implements the IInputDouble interface as well. This interface comes also from another, more abstract interface.

Those interfaces yield a better abstraction over the different kinds of port: AnalogInput, InputPort and RampGenerator.

The RampGenerator as virtual port.

As mentioned earlier, there’s a “false-wrapper” because it does NOT wrap any port, but it WORKS as it were a standard port. The benefit become from the interfaces abstraction.
In order to PRODUCE data overtime for the demo, I wanted something automatic but also “well-known”. I may have used a random-number generator, but…how to detect an error or a wrong sequence over a random stream of numbers? Better to rely on a perfectly shaped wave, being periodic, so I can easily check the correct order of the samples on the server, but any missing/multiple datum as well.
As a periodic signal you can choose whatever you want. A sine is maybe the most famous periodic wave, but the goal is testing the system, not having something nice to see. A simple “triangle-wave” generator, is just a linear ramp rising-then-falling, indefinitely.

Here is how a triangle-wave looks in a scope (it’s a 100 Hz, just to give an idea).

Of course, I may have used a normal bench wave-generator as a physical signal source, as in the snapshot right above. That would have been more realistic, but the expected wave period would have been too short (i.e. too fast) and the “changes” with consequent message upload too frequent. A software-based signal generator is well suited for very-long periods, like many minutes.

The HTTP client.

As described above, the data are sent to the server via normal (unsecured) HTTP. The Netduino Plus 2 does not offer any HTTP client, but some primitives which help to create your own.
Without digging much into, the client is rather simple. If you know how a basic HTTP transaction works, then you’ll have no difficulty to understand what the code does.

The above code derived from an old project, but here are actually just few lines of code of that release. However, I want to mention the source for who’s interested in.

As the Azure Mobile Services offer, there are two kind of APIs which can be called: table- (Database) and custom-API-operations. Again, I’ll detail those features on the next article.
The key-role is for the OperateCore method, which is a private entry-point for both the table- and the custom-API-requests. All Azure needs is some special HTTP-headers, which should contain the identification keys for gaining access to the platform.
The request’s content is just a JSON document, that is simple plain-text.

The main application.

When the program starts, first creates an instance of the Azure Mobile HTTP-Client (Zumo), then wraps all the port references within an array, for ease of management.
Notice that there are also two “special” ports called “RampGenerator”. In this demo there are two wave-generators with a period of 1200 and 1800 seconds, respectively. Their ranges are also slightly different, but just for less confusion in the data verification.
The ability to fit all the ports in a single array, then treat them as they were an unique entity is the benefit offered by the interfaces abstraction.

After the initialization, the program runs in a loop forever, and about every second all the ports are sampled. Upon any “concrete” variation, a JSON message is wrapped up with the new values, then sent to the server.

The composition of the JSON message is maybe the simplest part, because the Linq-way of my Micro-JSON library.
The led toggling is just a visual heartbeat-monitor.

The message schema.

In my mind, there should be more than just a single board. Better: a more realistic system should connect several devices, even different from each other. Then, each device should provide its own data, and all the data incoming into the server would compose a big-bunch of “variables”.
For this reason, it’s important to distinguish the data originating source, and a kind of “device-identification”, unique in the system, is included in every message.
Moreover, I’d think that the set of variables exposed by a device could be changed any time. For example, I may add some new sensors, re-arrange the input ports, or even adjust some data type. All that means the “configuration is changed”, and the server should be informed about that. That’s because there’s a “version-identification” as well.

Then are the real sensors data. It’s just an array of Javascript objects, each one providing the port (sensor) name and its value.
However, the array will include only the port marked as “changed”. This trick yields at least two advantages:

the message length carries only the useful data;

the approach is rather “loose-coupled”: the server synchronizes automatically.

Each variable serialization is accomplished by the relative method declared in the IInput interface. Here is an example for the analog port:

Conclusions.

It’s easy to realize that this project is very basic, and there are many sections that could be improved. For example, there’s no any rescue of the program when an exception is thrown. However, I wanted to keep the application at a very introductory level.
It’s time to wire your own prototype, because in the next article we’ll see how to set-up the Azure platform for the data elaboration.

On July 3, 1994 I subscribed for a small contest organized by RAI Radio Televisione Italiana. Anyone may submit his own software creation, and the prize was a TeleText module for PC.

I sent them my “Apple ][ emulator for PC” and I was awarded.

At that time, Internet still wasn’t known and most TV’s embed TeleText module, capable of receiving data on-the-air. Software broadcasting seemed as an unbelievable thing…then, in a few years, many of us were opening a web browser for surfing on the Internet.

My “real” Apple ][.

A step back to 1979.

My very first PC was a Commodore PET 2001: an unbelievable machine with a strange matrix-keyboard, a cassette-tape deck (storage) and a plain-green monitor on the top. Its engine was a 6502 CPU running at 1MHz and 8kB of RAM.

Yes, roughly an Arduino with an user-interface, but with the below exceptions:

an Arduino runs way faster;

the PET 2001 was particularly useful for the cold-winter days, due the relevant power consumption…

However, this PC was just for few months, then became too useless even for small games.

So, my “nominal” first PC was an Apple ][. In Europe it was marked “Europlus” (someone’d add “proudly built in Ireland”).

However, it came with the “usual” 6502 (actually an awesome CPU), still 1MHz, and 16kB of RAM (immediately upgraded to 48). The cassette-tape was replaced by a 5″ floppy-drive: each medium was capable of 140kB, that is probably less of this post. With a cost of 20000 Lire each (see below for a comparison), a Dysan floppy disk was the “best” on the market…at least for the humans.

I learn a lot on my Apple 2, both software and hardware.

With release of the Apple 2, the Cupertino-guys gave full-featured manuals, detailed hardware schematics, as well as ROM “BIOS” assembly dump. There was no point in the machine that wasn’t well known: hacking it was a real pleasure!

And I did it!…so many times!

Please, notice on the last picture the assembler listing signed by my myth, Steve Wozniak!

I designed several I/O hardware modules, where the most difficult part was the reproduction of the male-connection header: the PCB was the only way.

Along the huge yet worldwide success of Apple ][, they released the Apple //e, which started to fall fairly into the closeness, and so always more. That was the decay of the Apple company, and the rise of the IBM-PC, which moved in the same way as its predecessor: give away schematics and BIOS listings!
I still own my original Apple ][.

My “fake” Apple ][ (the emulator).

The advent of PC-XT changes almost everything but the general PC diffusion.

Whereas in the early ’80 there were maybe a dozen students having a PC at home (out of about 1500 of the tech high-school I was), within as low as ten years almost everyone own a PC in their house: mostly an IBM PC-compatible.

However, the Apple ][ was still in my heart!

Due to university guidelines, I started to learn Pascal and Fortran. However, Fortran was awful, but (Turbo-) Pascal was awesome, instead. I loved it so much that literally was able to create anything. Whereas the standard Pascal can’t reach something, just open an “asm” island, and mix high-level with assembler code.

No complex “includes”, “.h” or whatever, which I always hated and *still* hate. What are used for? I mean thirty years ago, where the PC resources are very limited, but…today?

I mean, no wonders at all that behind the success of C# there’s the creator of Turbo Pascal: Anders Hejlsberg.

So what?

Since my desktop wasn’t enough to place both the old Apple ][ and the PC-AT, the most “reasonable” decision was: “just create an Apple ][ emulator running in the PC-AT!”

It was the early ’90, and I own a 386 machine (I don’t remember the actual CPU speed). However, I loved coding this mixture of “Pasc-asm” that the result was still one of my best creation ever.

Below there is a piece of assembler related to the LDA (immediate) and LDA (indirect, X):

Keep going on in the box!

I was able to rescue the old emulator application running even on my today’s Windows 8 64-bit machine. It seems that the old-DOS programs aren’t working in a 64-bit environment, but there’s a solution: DosBox.

DosBox, as always, is the result of a crew of heroes, who thankfully remember that there are still people asking for dinosaur’s stuffs…dino, maybe, but still valuable!

I actually had no problems installing and running my application: I was a bit worried because the total NON-abstraction on write data on video, but…it worked well!

Enjoy this piece of history!

The price of an Apple ][ computer.

Here is the complete price details of the Apple ][ products, taken from a magazine of the november 1980.

NOTE: “IVA” is VAT, which was 15% in 1980.

Now, according to this reference, the salary of a generic factory worker was roughly 400.000 Lire. It means that an Apple ][ had an equivalent cost as 5 times a worker salary!